Samenvatting Fiancial Methods & Techinques
Inhoud
College 1 ................................................................................................................................................... 3
Regressies & OLS .................................................................................................................................. 3
CLRM Assumptions............................................................................................................................... 3
OLS in Matrix notitie ............................................................................................................................ 4
Hypothesis Testing: One coëfficiënt ..................................................................................................... 5
Hypothese Testing: Multiple Coëfficiënten .......................................................................................... 6
Setting up a model ............................................................................................................................... 8
Error types: ........................................................................................................................................... 8
College 2: Serial Correlation & Heteroskedasticity .................................................................................. 9
2.1 Non-Zero Mean Errors ................................................................................................................. 11
2.2 Heteroskedasticity ....................................................................................................................... 12
2.3 Correlated Errors .......................................................................................................................... 17
College 3: Endogeneity ........................................................................................................................... 22
3.1 Oorzaken van Endogeneity .......................................................................................................... 22
3.2 Probleem van Endogeniteit .......................................................................................................... 24
3.3 Oplossing: Instrumental Variable ................................................................................................. 24
3.4 Diagnose endogeniteit ................................................................................................................. 27
Lecture 4: Time Series Models ............................................................................................................... 28
4.1 Introductie Time Series ................................................................................................................ 28
4.2 AutoRegressive Models ................................................................................................................ 31
4.3 Moving Average model ................................................................................................................ 33
4.4 Partial ACF’s ................................................................................................................................. 34
4.5 Voorbeeld bepalen beste model .................................................................................................. 37
4.6 Forecasts ...................................................................................................................................... 39
Lecture 5: Niet-Sationairiteit .................................................................................................................. 41
5.1 Introductie niet-stationairiteit ..................................................................................................... 41
5.2 Trend-Stationary Proces ............................................................................................................... 43
5.3 Random Walk en t-statistieken .................................................................................................... 45
5.4 Wat gebeurt er als je de verkeerde oplossing gebruikt? ............................................................. 48
5.5 Diagnose van Unit root ................................................................................................................ 49
5.6 Co-integration .............................................................................................................................. 52
Lecture 6 GARCH .................................................................................................................................... 54
6.1 Garch-processes ........................................................................................................................... 55
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Inhoud
College 1 ................................................................................................................................................... 3
Regressies & OLS .................................................................................................................................. 3
CLRM Assumptions............................................................................................................................... 3
OLS in Matrix notitie ............................................................................................................................ 4
Hypothesis Testing: One coëfficiënt ..................................................................................................... 5
Hypothese Testing: Multiple Coëfficiënten .......................................................................................... 6
Setting up a model ............................................................................................................................... 8
Error types: ........................................................................................................................................... 8
College 2: Serial Correlation & Heteroskedasticity .................................................................................. 9
2.1 Non-Zero Mean Errors ................................................................................................................. 11
2.2 Heteroskedasticity ....................................................................................................................... 12
2.3 Correlated Errors .......................................................................................................................... 17
College 3: Endogeneity ........................................................................................................................... 22
3.1 Oorzaken van Endogeneity .......................................................................................................... 22
3.2 Probleem van Endogeniteit .......................................................................................................... 24
3.3 Oplossing: Instrumental Variable ................................................................................................. 24
3.4 Diagnose endogeniteit ................................................................................................................. 27
Lecture 4: Time Series Models ............................................................................................................... 28
4.1 Introductie Time Series ................................................................................................................ 28
4.2 AutoRegressive Models ................................................................................................................ 31
4.3 Moving Average model ................................................................................................................ 33
4.4 Partial ACF’s ................................................................................................................................. 34
4.5 Voorbeeld bepalen beste model .................................................................................................. 37
4.6 Forecasts ...................................................................................................................................... 39
Lecture 5: Niet-Sationairiteit .................................................................................................................. 41
5.1 Introductie niet-stationairiteit ..................................................................................................... 41
5.2 Trend-Stationary Proces ............................................................................................................... 43
5.3 Random Walk en t-statistieken .................................................................................................... 45
5.4 Wat gebeurt er als je de verkeerde oplossing gebruikt? ............................................................. 48
5.5 Diagnose van Unit root ................................................................................................................ 49
5.6 Co-integration .............................................................................................................................. 52
Lecture 6 GARCH .................................................................................................................................... 54
6.1 Garch-processes ........................................................................................................................... 55
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